机载LiDAR技术在复杂地形铁路定测阶段的应用研究

为提高新建铁路定测阶段测量工作效率,在某复杂地形新建铁路项目中,基于其使用机载LiDAR点云数据进行中线测量、横断面测量、地形图测绘等作业,并对数据精度进行分析比较。在LiDAR断面测量时,基于Terrasolid软件得到的成果数据冗余量大,提出一种改进的道格拉斯-普克算法,以达到既反映地形变化又减少断面点数量的效果。在项目横断面测量中,大量实测数据与LiDAR点云测量数据的对比分析表明,在植被稀疏的平地、丘陵地区,97.25%的断面点高差较差小于0.35 m, 100%的断面点高差较差小于0.5 m;在植被茂密的高山地区,73.33%的断面点高差较差小于0.35 m, 95.15%的断面点高差较差小于1.0 m。因此,在复杂地形铁路定测阶段,LiDAR数据生产宜采用内业生产为主,外业测量检核为辅的作业模式。     

车道识别过程中搜索车道线的方法

提出了一种在RO I(region of interest)即感兴趣区域中建立搜索窗口的车道识别算法,使其能够很好地处理非理想路况的各种不确定因素,并建立实时动态搜索窗口,除了能精确地追踪车道标志线之外,还能应用于弯路路况。运用LM edSquare曲线拟合算法提高了车道拟合过程的稳健性和精确性。由于RO I的建立,整个识别过程的计算量大大降低,适应实时性要求。     

Nonlinear Statistical Process Monitoring Based on Control Charts with Memory Effect and Kernel Independent Component Analysis

A novel nonlinear combination process monitoring method was proposed based on techniques with memory effect (multivariate exponentially weighted moving average (MEWMA)) and kernel independent component analysis (KICA). The method was developed for dealing with nonlinear issues and detecting small or moderate drifts in one or more process variables with autocorrelation. MEWMA charts use additional information from the past history of the process for keeping the memory effect of the process behavior trend. KICA is a recently developed statistical technique for revealing hidden, nonlinear statistically independent factors that underlie sets of measurements and it is a two-phase algorithm: whitened kernel principal component analysis (KPCA) plus independent component analysis (ICA). The application to the fluid catalytic cracking unit (FCCU) simulated process indicates that the proposed combined method based on MEWMA and KICA can effectively capture the nonlinear relationship and detect small drifts in process variables. Its performance significantly outperforms monitoring method based on ICA, MEWMA-ICA and KICA, especially for long-term performance deterioration.     

Efficient Accurate Context-Sensitive Anomaly Detection

For program behavior-based anomaly detection, the only way to ensure accurate monitoring is to construct an efficient and precise program behavior model. A new program behavior-based anomaly detection model, called combined pushdown automaton （CPDA） model was proposed, which is based on static binary executable analysis. The CPDA model incorporates the optimized call stack walk and code instrumentation technique to gain complete context information. Thereby the proposed method can detect more attacks, while retaining good performance.     

磁梯度法在钻孔桩钢筋笼长度检测中的研究

基桩工程中桩体内部钢筋笼长度是否按设计施工难以验证,以往的测试仪器及测试方法难以给予准确的判定。理论上,钢筋笼长度的变化反映了竖向磁性物理量的变化,因此沿钢筋笼轴向的磁梯度将产生明显的变化。根据这一特点结合某高速公路桩基工程中的应用实例对成桩后测试钢筋笼长度的原理及数据分析方法进行分析。理论分析及实例表明,钢筋笼磁梯度测试曲线与基桩低应变反射波法测试曲线有极其相似的特点。     

壁板坡特长隧道岩溶发育特征与超前探测

岩溶是壁板坡隧道的主要不良地质类型,研究如何进行准确预报及分析岩溶发育特征,对隧道施工安全具有重要意义。根据实际揭露的岩溶,从纵向和横向两个方面,全面分析壁板坡隧道岩溶的发育特征,根据形状将岩溶分为长条型、半球型和点孔型。介绍壁板坡隧道TSP、地质雷达、红外探水及超前水平钻探相结合的综合预报方法,以左线某处溶洞为例,论证该综合预报方法的准确性,证明是适用于特长隧道岩溶地质超前预报的可行方案。     

适用于轻轨系统的列车位置检测设备

对轻轨系统关键技术之一的位置检测设备进行探讨.分析常用的列车位置检测设备应用于轻轨系统的局限性,研究ARTJZ -2型计轴系统应用于各种钢轨和道床条件的工程实施方案,检测ARTJZ -2型计轴系统样机的功能、性能、安全,并对轻轨列车、汽车、行人混行模式下对系统的影响进行试验.试验结果表明,ARTJZ -2型计轴系统完全...     

土建工程施工中注浆技术的发展

从注浆技术的定义和分类、注浆材料、注浆方法、注浆效果的监控与检测等几个方面进行综述,介绍了土建工程施工中注浆技术的特点及发展趋势。     

多传感器的车辆信号灯故障动态监测方法研究

车辆信号灯对行车安全有重要的警示作用,现有的载货汽车不具备完善的信号灯故障动态监测预警功能。为在车辆行驶过程中对信号灯故障进行实时动态监测预警,设计了一种基于单片机控制、多传感器输入的车辆信号灯故障监测预警装置,基于信号灯工作原理的差异分别提出了信号灯故障0-1监测法、积分判别法和最小值判别法。以解放赛龙CA1169PK2L2EA80重型载货汽车为试验车,Freescale MC9S12XEP100单片机为车载终端构建了车辆信号灯故障监测试验系统平台。利用TES-1339R照度计分析了不同光照强度的外界光源对系统监测结果的影响,并采用故障预设的试验方法针对制动和转向信号灯分别采用不同的故障判别方法进行实车试验。试验结果表明:0-1监测法可以准确监测制动灯故障信号;积分判别法和最小值判别法适用于转向灯故障监测,最小值判别法较积分判别法监测转向灯故障分辨率高。该系统实现了车辆信号灯故障实时动态监测及声光预警,为预防由信号灯故障引发的道路交通事故提供了一种新方法。     

An analysis of the factors influencing differences in survey-reported and GPS-recorded trips

Recent advances in global positioning systems (GPS) technology have resulted in a transition in household travel survey methods to test the use of GPS units to record travel details, followed by the application of an algorithm to both identify trips and impute trip purpose, typically supplemented with some level of respondent confirmation via prompted-recall surveys. As the research community evaluates this new approach to potentially replace the traditional survey-reported collection method, it is important to consider how well the GPS-recorded and algorithm-imputed details capture trip details and whether the traditional survey-reported collection method may be preferred with regards to some types of travel. This paper considers two measures of travel intensity (survey-reported and GPS-recorded) for two trip purposes (work and non-work) as dependent variables in a joint ordered response model. The empirical analysis uses a sample from the full-study of the 2009 Indianapolis regional household travel survey. Individuals in this sample provided diary details about their travel survey day as well as carried wearable GPS units for the same 24-h period. The empirical results provide important insights regarding differences in measures of travel intensities related to the two different data collection modes (diary and GPS). The results suggest that more research is needed in the development of workplace identification algorithms, that GPS should continue to be used alongside rather than in lieu of the traditional diary approach, and that assignment of individuals to the GPS or diary survey approach should consider demographics and other characteristics.